DevOps pipelines are often automated, yet the operations side remains surprisingly manual. Here’s a framework to reduce toil using AIOps and the SECI model.
A clear-eyed breakdown of serverless costs — why they’re hidden, when they make sense, and how to choose between functions and containers before surprises hit your bill.
Integrate Octopus Deploy with Katalon to automate UI and API testing, gate releases, publish reports, and improve deployment reliability across environments.
A new volume type has recently joined the Kubernetes ecosystem: the image volume. This feature promises to change how we manage static data and configurations.
GPU-as-a-Service makes it easier to share accelerators, but it also raises concerns about isolation and security. This introduces a secure Kubernetes architecture.
MCP is production-ready for LLM-to-tool integration; A2A enables emerging multi-agent collaboration. They complement, not compete, and neither replaces Spark or Airflow.
AI-driven development is outpacing security teams. This piece examines where AI-powered security actually help, where they fail, and how teams can use them responsibly.
This article examines how integrating AI into the software development lifecycle (SDLC) is enabling teams to move from MVPs to large, resilient systems.
AI Agents perceive, reason, plan, and act autonomously using LLMs. This article breaks down the core components that power every agent and shows you how to build one.
This article provides a practical guide to building a fault-tolerant Google Cloud data pipeline architecture with Firestore, Pub/Sub, Dataflow, and BigQuery.
ML systems introduce security risks most teams aren’t prepared for. The piece explores emerging ML-specific threats and what effective MLSecOps looks like in practice.